GPU Droplets have GPUs in a single or 8 GPU configuration. They also come with two different kinds of storage: a boot disk for persistent data and a scratch disk for non-persistent data. Learn more about GPU Droplet plans and features.
We provide AI/ML-ready images for GPU Droplets that have drivers and software from AMD and NVIDIA preinstalled, as well as preconfigured 1-Click Models powered by Hugging Face. You can also create GPU Droplets with existing Droplet images, but you need to manually install drivers and other software to use the GPUs.
If you are a newer DigitalOcean customer, we may charge your team’s primary payment method partway through the monthly billing cycle when you create GPU Droplets, but your total cost is not increased. This is a precautionary measure to prevent abuse of our platform.
Create a GPU Droplet in the Control Panel
After you log in to the control panel, click the green Create button in the top right to open the Create menu, then click GPU Droplets to go to the GPU Droplet creation page.
Create a GPU Droplet with the resources you choose.
This page has similar sections as the regular Droplet creation page, like choosing a datacenter region and SSH keys, and some different options:
Once you finish selecting your options, click Create GPU Droplet. GPU Droplets generally take longer than non-GPU Droplets to initialize, particularly for 8 GPU Droplets, so allow some time for this process to finish.
Create a GPU Droplet Using the DigitalOcean API or CLI
When creating a GPU Droplet using the DigitalOcean API or CLI, you need to provide values for:
- The
region, the string for the desired datacenter.
- The
size, the slug that specifies the Droplet plan.
- The
image, the slug that specifies the base image.
You can view slugs for all GPU Droplet plans and more information on AI/ML-ready and inference-optimized images.
How to Create a New Droplet Using the DigitalOcean CLI
- Install
doctl, the official DigitalOcean CLI.
- Create a personal access token and save it for use with
doctl.
- Use the token to grant
doctl access to your DigitalOcean account.
- Finally, run
doctl compute droplet create. Basic usage looks like this, but you can read the usage docs for more details:
doctl compute droplet create <droplet-name>... [flags]
example-droplet with a two vCPUs, two GiB of RAM, and 20 GBs of disk space. The Droplet is created in the nyc1 region and is based on the ubuntu-20-04-x64 image. Additionally, the command uses the --user-data flag to run a Bash script the first time the Droplet boots up:
doctl compute droplet create example-droplet –size s-2vcpu-2gb –image ubuntu-20-04-x64 –region nyc1 –user-data $’#!/bin/bash\n touch /root/example.txt; sudo apt update;sudo snap install doctl'
Please note: In Windows Powershell, the example command would be the following instead:
```shell
doctl compute droplet create example-droplet --size s-2vcpu-2gb --image ubuntu-20-04-x64 --region nyc1 --user-data "#!/bin/bash`n touch /root/example.txt; sudo apt update;sudo snap install doctl"
```
How to Create a New Droplet Using the DigitalOcean API
- Create a personal access token and save it for use with the API.
- Send a POST request to
https://api.digitalocean.com/v2/droplets.
cURL
Using cURL:
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $DIGITALOCEAN_TOKEN" \
-d '{"name":"example.com","region":"nyc3","size":"s-1vcpu-1gb","image":"ubuntu-20-04-x64","ssh_keys":[289794,"3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"],"backups":true,"ipv6":true,"monitoring":true,"tags":["env:prod","web"],"user_data":"#cloud-config\nruncmd:\n - touch /test.txt\n","vpc_uuid":"760e09ef-dc84-11e8-981e-3cfdfeaae000"}' \
"https://api.digitalocean.com/v2/droplets"
Go
Using Godo, the official DigitalOcean API client for Go:
import (
"context"
"os"
"github.com/digitalocean/godo"
)
func main() {
token := os.Getenv("DIGITALOCEAN_TOKEN")
client := godo.NewFromToken(token)
ctx := context.TODO()
createRequest := &godo.DropletCreateRequest{
Name: "example.com",
Region: "nyc3",
Size: "s-1vcpu-1gb",
Image: godo.DropletCreateImage{
Slug: "ubuntu-20-04-x64",
},
SSHKeys: []godo.DropletCreateSSHKey{
godo.DropletCreateSSHKey{ID: 289794},
godo.DropletCreateSSHKey{Fingerprint: "3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"}
},
Backups: true,
IPv6: true,
Monitoring: true,
Tags: []string{"env:prod","web"},
UserData: "#cloud-config\nruncmd:\n - touch /test.txt\n",
VPCUUID: "760e09ef-dc84-11e8-981e-3cfdfeaae000",
}
Ruby
Using DropletKit, the official DigitalOcean API client for Ruby:
require 'droplet_kit'
token = ENV['DIGITALOCEAN_TOKEN']
client = DropletKit::Client.new(access_token: token)
droplet = DropletKit::Droplet.new(
name: 'example.com',
region: 'nyc3',
size: 's-1vcpu-1gb',
image: 'ubuntu-20-04-x64',
ssh_keys: [289794,"3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"],
backups: true,
ipv6: true,
monitoring: true,
tags: ["env:prod","web"],
user_data: "#cloud-config\nruncmd:\n - touch /test.txt\n",
vpc_uuid: "760e09ef-dc84-11e8-981e-3cfdfeaae000",
)
client.droplets.create(droplet)
Python
Using PyDo, the official DigitalOcean API client for Python:
import os
from pydo import Client
client = Client(token=os.environ.get("DIGITALOCEAN_TOKEN"))
req = {
"name": "example.com",
"region": "nyc3",
"size": "s-1vcpu-1gb",
"image": "ubuntu-20-04-x64",
"ssh_keys": [
289794,
"3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"
],
"backups": True,
"ipv6": True,
"monitoring": True,
"tags": [
"env:prod",
"web"
],
"user_data": "#cloud-config\nruncmd:\n - touch /test.txt\n",
"vpc_uuid": "760e09ef-dc84-11e8-981e-3cfdfeaae000"
}
resp = client.droplets.create(body=req)
